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Tangentially, watching the pace of papers coming out in machine learning is insane. It's so fast, people may literally cite powerpoint slides when the paper do
by return0 11y ago
Tangentially, watching the pace of papers coming out in machine learning is insane. It's so fast, people may literally cite powerpoint slides when the paper doesnt exist yet. The culture of openness seems to have fostered this insane pace. Contrasting that with the reclusive culture of life sciences explains why there is slow progress there.
- hackuser 11y agoIf someone with technical expertise wanted to keep up on this field, but it wasn't their profession - i.e., they don't need to know every detail and don't have time to read a lot - what would be a good source?
- p1esk 11y agoFollow Yann Lecun's posts on Facebook.
- jasonwatkinspdx 11y agoI think what you're saying is broadly true, but I'd moderate it a bit by pointing out that reproducing and extending research in software is a heck of a lot simpler and faster than working in topic areas that require physical experiments and processes.
- snowwrestler 11y agoArent's the systems being studied in life sciences much more complex than in machine learning? Consider the problem of protein folding, which has taken up many a processor cycle over the past decade or so. And that's just a tiny sliver of life sciences.
- p1esk 11y agoML and life sciences operate on different abstraction levels. It's like asking which is more complex: quantum mechanics or algebraic topology.